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brain_segmentation

cnn-3d-images-tensorflow

3D image classification using CNN (Convolutional Neural Network)

colonogram-enhancement

datasciencecoursera

This repository created to use Data science project on Coursera

datasharing

The Leek group guide to data sharing

deep-admm-net

deep-learning-for-medical-applications

Deep Learning Papers on Medical Image Analysis

deep_mri_brain_extraction

3D convolutional neural network for MRI brain extraction

deeplearning.ai

Some work of Andrew Ng's course on Coursera

deepmedic

Efficient Multi-Scale 3D Convolutional Neural Network for Brain Lesion Segmentation

dlib

A toolkit for making real world machine learning and data analysis applications in C++

dlvcnptel

Tutorials for DLVC NPTEL MOOC

enresnet

New deep learning model for x-ray image enhancement.

helloworld

## This is a markdown file

image-enhancement_colonogram

Colonoscopy image enhancement

intro-to-dl

Resources for "Introduction to Deep Learning" course.

learnopencv

Learn OpenCV : C++ and Python Examples

livianet

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

machinelearning-deeplearning-code-for-my-youtube-channel

The full collection of all codes for my Youtube Channel segregated as per topic.

mammogram-segmentation-by-ifssmr

mastering-ml-w-python-in-six-steps

Source code for 'Mastering Machine Learning with Python in Six Steps' by Manohar Swamynathan

medical-data

models

Models and examples built with TensorFlow

programmingassignment2

Repository for Programming Assignment 2 for R Programming on Coursera

retina-features

Project for segmentation of blood vessels, microaneurysm and hardexudates in fundus images.

retina-vesselnet

A DenseBlock-Unet for Retinal Blood Vessel Segmentation

retinal-exudates-detection

exudates detection using hybrid approach (Image Morphology & Machine Learning)

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

swarupg1

Config files for my GitHub profile.

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs